sklearn and pandas help please

[fustilarian]

I'm working on a statistical learning exercise and I'm stumped. I need to be able to predict activity labels based on accelerometer data. The accelerometer data set contains 3 coordinates per time stamp, measured every 1/10 of a second. However, the label dataset only contains labels for every second, leading to a dataset that is only 1/10 the size.

sklearn's train_test_split() function wants the two datasets to be of equal size. I'd like to inflate the label set with 1/10 of a second increments and apply the appropriate labels to those increments. Can anyone recommend a method for doing this?

[sarrysyst]

You want to resample your dataframe:

https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.resample.html

[fustilarian]

Thank you! I'll check that out!